| Summary: | Personality inventories in South Africa are challenged with many factors restricting unbiased and fair measurement. The Employment Equity Act clearly stipulates that all psychometric measuring instruments should be proven bias free, equivalent, and fair. Most of the current inventories utilised in South Africa are imported from Europe and/or the United States of America, and these instruments are translated into either English or Afrikaans, which restricts the language proficiency factor of respondents from other language groups. There are 11 official language groups in South Africa; people also differ regarding race, culture, socioeconomic status, and educational backgrounds. All of these factors are not always properly accounted for in the standardisation of imported inventories - which limits their appropriate employment in the South African context. The objective of this study was to uncover the personality structure of each of the 11 language groups in South Africa, and to identify the shared and unique personality dimensions of the different language groups. From this structure, an instrument will be developed to measure personality in such a way that it will meet the Employment Equity Act.
A qualitative research design was used in this study. Quasi-sampling («=1308j was implemented in order to identify participants from each of the 11 language groups, which differed from each other with regard to age, gender, and socioeconomic status. Following the lexical approach, structured interviews were conducted in the native language of the participants to gather information about personality-descriptive terms. The results of the interviews were transcribed and captured in Excel, and sent to language experts for language editing and translation into English. Ambiguous, superfluous and non-personality terms were removed from the data. Following this process, more than 50 000 personality-descriptive terms were identified. Content analysis was utilised in order to interpret the personality-
descriptive terms to personality dimensions. Language and cultural experts were employed in order to validate the initial interpretations. The 50 000 descriptive terms were reduced to 190 personality dimensions through the use of cluster analysis. The analysis included the grouping of synonyms and antonyms, together with the use of dictionaries, literature and knowledge about content. The 190 dimensions were also divided into those that are common (shared by all 11 language groups), semi-common (shared by seven to ten of the language groups), semi-specific (shared by two to six of the language groups), and language-specific (unique to a particular language group). It was discovered that 78 dimensions were common, 69 semi-common, 32 semi-specific, and only 11 were language-specific. Most of the personality dimensions seem to be shared by the language groups, rather than to be unique.
These 190 dimensions were clustered further in order to build the indigenous personality structure. Similar methods from the initial clustering phase were implemented. Clustering concluded 37 sub-clusters, which consisted of two to ten dimensions, and nine overall clusters consisting of two to six sub-clusters. These nine clusters are Extroversion, Soft-heartedness, Conscientiousness, Emotional stability, Intellect, Openness, Integrity, Relationship harmony, and Facilitating. Many indigenous aspects are evident, as well as universal aspects within the structure. === Thesis (Ph.D. (Industrial Psychology))--North-West University, Potchefstroom Campus, 2009.
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